code: def test_cdmd_float32(self):
      # Define time and space discretizations
      x = np.linspace(-5, 5, 50)
      t = np.linspace(0, 8 * np.pi, 20)
      dt = t[2] - t[1]
      X, T = np.meshgrid(x, t)
      # Create two spatio-temporal patterns
      F1 = 0.5 * np.cos(X) * (1.0 + 0.0 * T)
      F2 = ((1.0 / np.cosh(X)) * np.tanh(X)) * (
          2.0 * np.exp(1j * 2.8 * T)
      )
      D = F1 + F2
      a = np.array(D.real, np.float32, order="F")
      a_gpu = gpuarray.to_gpu(a)
      dmdf_gpu, dmdb_gpu, dmdv_gpu, dmdomega = linalg.dmd(
          a_gpu,
          k=2,
          modes="exact",
          return_amplitudes=True,
          return_vandermonde=True,
      )
      f_gpu, b_gpu, v_gpu, omega = rlinalg.cdmd(
          a_gpu,
          k=2,
          c=10,
          modes="exact",
          return_amplitudes=True,
          return_vandermonde=True,
      )
      assert np.allclose(dmdomega.get(), omega.get(), atol_float32)
  
imports: from unittest import main, makeSuite, skipUnless, TestCase, TestSuite
  import pycuda.autoinit
  import pycuda.gpuarray
  import numpy
  from numpy.testing import assert_raises
  import skcuda.linalg
  import skcuda.rlinalg
  import skcuda.misc
label_desc: Use image node_id 15 for calling the test_rlinalg obj's underlying member method code with example usage: obj.test_cdmd_float32() without return types